Systems Analysis of Introgressive Hybridization Among Trout: Assessing Crossing, Fitness, Dispersal Rates, and Landscape Connectivity As Drivers of Genetic Structure in Hybridized Populations

Introgressive hybridization with introduced rainbow trout (Oncorhynchus mykiss) is one of the major threats to cutthroat trout (O. clarki) across their entire native range and has been the topic of fisheries research for decades in the northern Rocky Mountains, USA. Although large datasets have been collected to document the spread of introgression across stream networks, these datasets are not typically used to assess the importance of different mechanisms that drive the spread of non-native genes across stream networks. In the last year, we developed a novel, system-level, individual-based simulation model aimed at investigating and quantifying the relative importance of the four drivers critical to the spread of non-native genes across heterogeneous landscapes, namely: i) propensity to crossbreed; ii) fitness; iii) dispersal rates, and; iv) landscape connectivity. Moreover, the simulation can be applied to improve current field data sampling strategies by revealing the type and quality of field data necessary to detect and estimate the effects of each driver of introgressive hybridization across a stream network. Recently we conducted analyses designed to detect the sensitivity of different aspects of introgression (such as rate of spread and changes in introgression levels at single locations over time) to the four aforementioned drivers of gene movement. Results of these analyses, suggest that each driver affects patterns of introgression across networks in a different way, and that the drivers’ effects are detectable and measurable using specific field data. For example, landscape connectivity patterns influence the susceptibility to hybridization of single sub-populations within a network, and dispersal rates influence the rate of genetic homogenization of river networks over time. Thus, our study shows that by measuring specific aspects of non-native gene distribution across stream networks and the inter-generational differences in non-native gene frequency, we may be able to quantify the importance of each driver as a control on the overall spread of introgressive hybridization, therefore increasing our ability to develop effective strategies to manage the spread of non-native genes in river networks.